Abstract: Approaching mixed-integer black box optimization (MI-BBO) problems requires algorithms that can handle both the continuous as well as the discrete variables. Recent work in this area has ...

Solving optimization problems is challenging for existing digital computers and even for future quantum hardware. The practical importance of diverse problems, from healthcare to financial ...

Abstract: Quantum random number generators (QRNGs) harness quantum mechanical unpredictability to produce true randomness, which is crucial for cryptography and secure communications. Among various ...

Social Networks have been in continuous growing during the last decades. The huge amount of information and applications has led to an increase in the interest of scientists and practitioners in the ...

The potential of quantum computers is currently thwarted by a trade-off problem. Quantum systems that can carry out complex operations are less tolerant to errors and noise, while systems that are ...

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Mixed-variable problems are inevitable in engineering. However, few researches pay attention to discrete variables. This paper proposed a mixed-variable experimental design method (ODCD): first, the ...

Quantum annealing (QA) can be competitive to classical algorithms in optimizing continuous-variable functions when running on appropriate hardware, show researchers from Tokyo Tech. By comparing the ...

Quantum annealing (QA) is a cutting-edge algorithm that leverages the unique properties of quantum computing to tackle complex combinatorial optimization problems (a class of mathematical problems ...